Triple
T22230347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The River (1951 film) |
E549448
|
entity |
| Predicate | filmingLocation |
P40
|
FINISHED |
| Object | Bengal |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Bengal | Statement: [The River (1951 film), filmingLocation, Bengal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bengal Context triple: [The River (1951 film), filmingLocation, Bengal]
-
A.
Bengal
chosen
Bengal is a historical and cultural region in the eastern part of the Indian subcontinent, known for its rich literary, artistic, and political heritage and now divided between Bangladesh and the Indian state of West Bengal.
-
B.
Bengal
The Bengal is a tiger-themed school mascot commonly used to represent athletic teams and school spirit.
-
C.
La Banga
La Banga is a musical artist known for collaborating with the group The Movement.
-
D.
Bangála
Bangála is an alternative name for Bangala, which can refer to various places, languages, or cultural entities associated with Central or West Africa depending on context.
-
E.
Indu Banga
Indu Banga is an Indian academic and historian known for her work on the social and economic history of Punjab and North India.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e11e4102b881909cf47d3768e25c19 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12bf2a26c81908aaf614d7c75e219 |
completed | April 28, 2026, 9:51 p.m. |
Created at: April 16, 2026, 8:37 p.m.